I-Corps: Accurate GPS-free Navigation and Localization

I-Corps：准确的无 GPS 导航和定位

• 批准号: 1740544
• 负责人: Suman Chakravorty
• 金额: $ 5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1740544&HistoricalAwards=false
• 关键词: Corps; Accurate; GPS; free; Navigation

The broader impact/commercial potential of this I-Corps project is to develop autonomous navigation technology that will enable systems to robustly operate in uncertain environments without a Global Positioning System (GPS). The project is a result of a confluence of astronomy, aerospace, computational science and artificial intelligence. Commercialization of this technology has the potential to revolutionize space exploration, self-driving cars, Unmanned Aerial Vehicles (UAVs) and other such systems which need accurate position estimation. A key advantage of this project's technology is enhanced cybersecurity as it does not rely on external signals for navigation. Further, this project will contribute open-source software to the scientific community. It is envisioned that development of a software toolbox that integrates with the popular ROS (Robot Operating System) library will allow researchers to simulate autonomous navigation without GPS.This I-Corps project is a result of research into the problem of Simultaneous Localization and Mapping (SLAM). In SLAM, a robot is not given prior knowledge of its environment, it must use its sensory data and actions to simultaneously build a map of its environment and position itself within its uncertain map. Competing methods in this area exhibit positioning errors which may be unsuitable for long-term navigation. The work developed here shows that by fusing orientation sensing with short-range sensing, the system attain a simplification of the underlying optimization problem. This allows fast and globally optimal solutions. In this approach, a vehicle uses a camera to track celestial bodies in the sky which allows the vehicle to estimate its orientation in space, this information is fused with short-range sensors such as lasers and cameras which track features in vicinity of the vehicle. Using the proposed approach, a system can achieve 100x improvement in position error over existing methods.

这个i-Corps项目的更广泛的影响/商业潜力是开发自主导航技术，使系统能够在没有全球定位系统(GPS)的情况下在不确定的环境中稳健运行。该项目是天文学、航空航天、计算科学和人工智能相结合的结果。这项技术的商业化有可能给太空探索、自动驾驶汽车、无人机(UAV)和其他需要准确位置估计的此类系统带来革命性的变化。该项目技术的一个关键优势是增强了网络安全，因为它不依赖外部信号进行导航。此外，该项目将为科学界贡献开源软件。据设想，开发一个与流行的ROS(机器人操作系统)库集成的软件工具箱将允许研究人员在没有GPS的情况下模拟自主导航。I-Corps项目是对同步定位和地图绘制(SLAM)问题的研究结果。在SLAM中，机器人没有获得关于其环境的先验知识，它必须使用其感官数据和动作来同时建立其环境的地图，并在其不确定的地图中定位自己。这一领域的竞争方法显示出定位误差，这可能不适合长期导航。这里的工作表明，通过融合方向传感和短程传感，该系统实现了基本优化问题的简化。这就实现了快速且全局最优的解决方案。在这种方法中，飞行器使用相机来跟踪天空中的天体，从而使飞行器能够估计其在空间中的方向，这些信息与跟踪飞行器附近特征的激光和相机等短程传感器融合。使用该方法，系统的位置误差比现有方法提高了100倍。